离散线性水文系统模型及其参数估算*

本文介绍了连续和离散线性水文系统模型以及它们之间的对应关系,论述了离散线性水文系统模型的稳定性,其参数之间的对应关系,着重说明了现有常用几种水文模型均是离散水文系统模型的特例,提出了离散线性水文系统模型参数确定的四种方法,并给出了算例。     

农业干旱业务化监测研究进展与展望

业务化农业干旱监测系统是农业干旱监测和预测以及农业风险评价和防范的有力工具,为了更好地促进农业干旱业务化监测的发展,系统回顾了基于气象变量、土壤湿度、植被状态和多变量等4类常用干旱指数,详细分析了美国、中国、欧洲和联合国粮食及农业组织等业务化农业干旱监测系统的特征,讨论了业务化农业干旱监测系统中存在的问题：如数据的质量及融合不稳定、综合干旱指数的构建不确定、监测的时间分辨率有待提高、缺乏考虑水文条件以及作物的生长过程等影响的问题。展望了未来农业干旱业务化监测,应从利用多源数据监测干旱、构建综合指标时需考虑区域时空差异及不同指标间的累积性和滞后性、加强机器及深度学习在综合指标构建中的作用、发展日时间尺度监测干旱以应对骤旱事件的发生、强化作物生长过程模型和先进的技术手段在干旱监测中的作用等方面深入发展。     

水文系统不确定性分析方法及应用研究进展

水文系统是一个复杂的系统,包含了很多不确定性因素,增加了精确模拟和预测水文过程的困难。为了提高计算结果的可靠性,水文系统的不确定性分析已成为当前研究的热点。本文对水文系统不确定性分析方法及应用研究进展进行了分类综述,介绍了它们的数学原理、操作程序和应用现状,并对值得进一步研究的问题进行了展望,指出加强水文过程机理研究、在水文循环过程更多环节上拓宽不确定性研究、以及将多种不确定性分析方法进行综合是未来的研究趋势。     

A spatial approach to forest‐management optimization: linking GIS and multiple objective genetic algorithms

Forest‐management decision‐support systems are largely monolithic structures. Spatial details are left out during the optimization process and are elaborated during the operational planning. This might produce misleading results and plans that are impossible to implement. In this paper, a forest‐management spatial decision‐support systems is presented, in which spatial formulation needed for wildlife models is included during the optimization process. To this end, a multiple‐objective genetic algorithm is combined with a geographical information system. An online spatial evaluation of the objective functions is made possible. This is illustrated by a pilot study in Kirkhill forest, Aberdeen.     

Design of a view-based DSS for location planning

Abstract.

The traditional approach in DSS falls short of providing a highly interactive problem solving environment for planning. Often, cumbersome procedures are required to implement optional plans and obtain feedback information. In dynamic graphic systems, the user is able to view different linked graphic representations (e.g., spatial or statistical graphs) of statistical data and interact (e.g., selecting items) with these graphics. In this paper we describe the design of a DSS for planning facility locations, which uses principles of dynamic graphics to achieve a highly interactive problem solving environment. As in dynamic graphic systems, the user interacts with the DSS through active and linked views. However, where views in dynamic graphics are different representations of a given dataset, the views in the DSS are active data structures describing the facility system to be planned from different perspectives. The declarative and procedural forms of knowledge involved are identified by a logical analysis of planning problems. A frame-based formalism is proposed to represent the knowledge contained in the views. The main advantage of this view-based approach is that it offers the user a highly flexible and interactive environment for performing ‘what-if’ analyses.     

Verification of the motion fields over Southeast Asia by the Florida State University (FSU) superensemble forecast

The Florida State University (FSU) multimodel superensemble forecast is evaluated against several other operational weather models for the Southeast Asia region. The superensemble technique has demonstrated its exceptional skills in forecasting precipitation, motion and mass fields compared to either individual global operational or ensemble mean forecasts. The motion field investigation for the season of 2001 reveals that the superensemble forecasts are closer to the observed data compared to the other global member operational models through its low systematic errors at the 850 hPa level. The FSU multimodel superensemble forecasts exhibit the lowest root mean square errors (RSMEs), the highest correlation against the best observed data and the lowest systematic errors compared to the other operational model members. These forecasts have the potential to provide better daily weather predictions over the Southeast Asia region, particularly during the early northeast monsoon that often causes heavy rainfall in the equatorial part of the Southeast Asia region.     

Modeling tropical river runoff: A time dependent approach

Forecasting of rainfall and subsequent river runoff is important for many operational problems and applications related to hydrology. Modeling river runoff often requires rigorous mathematical analysis of vast historical data to arrive at reasonable conclusions. In this paper we have applied the stochastic method to characterize and predict river runoffofthe perennial Kulfo River in southem Ethiopia. The time series analysis based auto regressive integrated moving average （ARIMA） approach is applied to mean monthly runoff data with 10 and 20 years spans. The varying length of the input runoff data is shown to influence the forecasting efficiency of the stochastic process. Preprocessing of the runoff time series data indicated that the data do not follow a seasonal pattern. Our forecasts were made using parsimonious non seasonal ARIMA models and the results were compared to actual 10-year and 20-year mean monthly runoff data of the Kulfo River. Our results indicate that river runoff forecasts based upon the 10-year data are more accurate and efficient than the model based on the 20-year time series.     

Working rivers: the geomorphological legacy of English freshwater mills

Freshwater mills historically were found throughout England serving a wide variety of uses. The decline in the need for water power over the last 100 years saw a reduction in the number of operational mills. Despite this decline, the associated river structures were rarely removed and many of these have exceeded their design life and have failed or are now starting to fail, with important geomorphological implications for the river. This paper investigates the geomorphological impacts of mills and their structures on English rivers, and considers their legacy for the contemporary management of these systems.     

南极数值天气预报应用与研究进展

多个业务化的全球预报模式和有限区域预报模式应用于南极地区,已经成为南极天气预报和南极气候诊断研究的主要工具.现今南极地区的数值天气预报模式在模拟南极大气环流和天气系统方面性能不够理想,原因是多方面的:南极天气气候的特殊性(包括边界层的参数化、中尺度气旋等)、模式对南极复杂地形的描述不够充分、由于缺乏观测资料而使得模式的...     

On the importance of rock thermal conductivity and heat flow density in basin and petroleum system modelling

Basin and petroleum systems are routinely modelled to provide qualitative and quantitative assessments of a hydrocarbon play. The importance of the rock thermal properties and heat flow density in thermal modelling the history of a basin are well-known, but little attention is paid to assumptions of the thermal conductivity, present-day heat flow density and thermal history of basins. Assumed values are often far from measured values when data are available to check parameters, and effective thermal conductivity models prescribed in many basin simulators require improvement. The reconstructed thermal history is often justified by a successful calibration to present-day temperature and vitrinite reflectance data. However, a successful calibration does not guarantee that the reconstruction history is correct. In this paper, we describe the pitfalls in setting the thermal conductivity and heat flow density in basin models and the typical uncertainties in these parameters, and we estimate the consequences by means of a one-dimensional model of the super-deep Tyumen SG-6 well area that benefits from large amounts of reliable input and calibration data. The results show that the entire approach to present-day heat flow evaluations needs to be reassessed. Unreliable heat flow density data along with a lack of measurements of rock thermal properties of cores can undermine the quality of basin and petroleum system modelling.     

Derivative‐Neural Spectroscopy for Hyperspectral Bathymetric Inversion*

Bathymetry is an important variable in scientific and operational applications. The research objectives in this study were to estimate bathymetry based on derivative reflectance spectra used as input to a multilayer perceptron artificial neural network (ANN) and to evaluate the efficacy of field and simulated training/testing data. ANNs were used to invert reflectance field data acquired in optically shallow coastal waters. Results indicate that for the simulation‐based models, nonderivative spectra yielded more accurate bathymetry retrievals than the derivative spectra used as ANN input. However, for the empirical field‐based models, derivative spectra were superior to nonderivative spectra as ANN input. This study identifies circumstances under which derivative spectra are useful in bathymetry estimation, and thus increases the likelihood of obtaining accurate inversions.     

论地理信息系统及其在地理学中的地位

地理信息系统技术的兴起代表了地理学发展的一个重要方向。地理信息系统是一门处理地理(空间)数据的综合信息技术,它属于技术地理学的范畴,它为资源与环境的管理和规划以及地理学的研究提供了一个革命性工具。另一方面,地理信息系统的建立和应用又依赖于地理学理论和实用模型的发展。进一步勾通地理信息系统与空间分析之间的关系是目前促进地理信息系统发展的重要课题。     

元胞模型在地貌演化模拟中的应用浅析

元胞自动机是一个时空离散的动力学模型,是复杂系统的研究方法之一。从80年代后期开始,在许多领域都得到广泛的应用与发展。地貌是一个非线性动态复杂系统,元胞自动机模型(或更广意义上的元胞模型)为研究复杂地貌系统的动态演化提供了新的方法论工具。本文根据近些年国内外该领域的研究成果,对元胞模型在地貌演化模拟中的应用及进展进行了探讨,并分析了元胞模型方法在地貌演化模拟中的优势和不足。     

A treatise on the use of geostatistics for the characterization of nonrenewable resources

Five decades of geostatistical development are reviewed to summarize the state of the art for spatial interpolation vis-à-vis kriging or a form thereof. Although a search of the literature reveals a variety of kriging methods, there are but two infrastructures for geostatistical interpolation: simple cokriging, for estimating a single variable using two variables, and generalized cokriging, for estimating one or more variables using the same number of variables that are estimated. The many forms of kriging are varieties of these two interpolation infrastructures. This notion is emphasized to aid the selection of an appropriate interpolation model for a nonrenewable resource. These models are discussed, and literature for the models and for applicable software is cited. Additionally, all aspects of spatial interpolation are discussed, including the adequacy of spatial sampling, distribution characteristics of spatial samples, semivariograms, search parameters, and selection of interpolation models in conformance with spatial data characteristics. Finally, the relationship between interpolation and raster-based geographic information systems is emphasized.     

Reservoir Modeling by Data Integration via Intermediate Spaces and Artificial Intelligence Tools in MPS Simulation Frameworks

Conditioning stochastic simulations are very important in many geostatistical applications that call for the introduction of nonlinear and multiple-point data in reservoir modeling. Here, a new methodology is proposed for the incorporation of different data types into multiple-point statistics (MPS) simulation frameworks. Unlike the previous techniques that call for an approximate forward model (filter) for integration of secondary data into geologically constructed models, the proposed approach develops an intermediate space where all the primary and secondary data are easily mapped onto. Definition of the intermediate space, as may be achieved via application of artificial intelligence tools like neural networks and fuzzy inference systems, eliminates the need for using filters as in previous techniques. The applicability of the proposed approach in conditioning MPS simulations to static and geologic data is verified by modeling a real example of discrete fracture networks using conventional well-log data. The training patterns are well reproduced in the realizations, while the model is also consistent with the map of secondary data.     

基于GIS的细胞自动机模型与人地关系的复杂性探讨

探讨人地非线性关系可以揭示地理系统空间复杂性的许多简单本质 ,具有重要的理论意义和实践价值。以地理信息系统 (GIS)为技术支持 ,建立以细胞自动机 (CA)为核心的综合集成模型 ,将成为人地关系复杂性研究的主要方向。建议在CA GIS集成技术的基础上 ,一方面引入人工神经网络、进化算法、多重智能体系 (MAS)以及后现代数学分析方法 ,另一方面面向具体研究对象开发包括自然、人文地理要素在内的集成区域动力学模型 ,据此发展智能化综合集成模型体系 ,形成人地关系复杂性的模拟研究实验室。本文提出了开发智能化CA GIS模拟方法的初步设想。     

Real-time data collection quality assurance models in three-dimensional spatial information systems

Abstract

Databases used in geographical information systems must be supplied with current data. Maps are usually out of date when they are published. Satellite imagery and aerial photographs supply up-to-date three-dimensional data. Three different models for real-time quality assurance control in three-dimensional data collection for geographical information systems are discussed. Emphasis is placed on the visual detection of ‘blunders’ in three-dimensional data. One data collection quality assurance model has been implemented in the Photogrammetric Analysis Laboratory at Purdue University. An example from this system is given and the precision and speed of digitization of three-dimensional data are discussed.     

Spatial Modeling of Geometallurgical Properties: Techniques and a Case Study

High-resolution spatial numerical models of metallurgical properties constrained by geological controls and more extensively by measured grade and geomechanical properties constitute an important part of geometallurgy. Geostatistical and other numerical techniques are adapted and developed to construct these high-resolution models accounting for all available data. Important issues that must be addressed include unequal sampling of the metallurgical properties versus grade assays, measurements at different scale, and complex nonlinear averaging of many metallurgical parameters. This paper establishes techniques to address each of these issues with the required implementation details and also demonstrates geometallurgical mineral deposit characterization for a copper–molybdenum deposit in South America. High-resolution models of grades and comminution indices are constructed, checked, and are rigorously validated. The workflow demonstrated in this case study is applicable to many other deposit types.